Computers, Networks & Communications

Every day, cloud computing—which stores user data online—becomes more and more popular. Instead of being aware of security risks, the main goal of a cloud-based system is to use the internet as a storage medium. Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are the three primary categories of cloud computing models. But as cloud computing has gotten more popular, security has grown to be a major worry. The difficulties with data storage in various cloud computing scenarios are examined in this research. It suggests using the Internet Protocol Security (IPsec) architecture as the foundation for the Security Encryption Privacy (SEP) paradigm. To improve security and stop assaults on cloud storage, it generates and encrypts data using the RSA algorithm and public key cryptography. In addition, our suggested approach is contrasted with alternative security models. This study’s primary goal is to comprehend cloud computing.

Wireless sensor networks (WSNs) offer advantages in deployment flexibility and affordability due to their compact size and low cost. However, real-world WSN implementations face challenges, particularly regarding energy consumption. The limited battery capacity of sensor nodes restricts their operational lifespan, often resulting in; it is difficult to periodically replace the batteries in sensor nodes or recharge them, which reduces the system's overall operating time. To address the energy consumption challenge, WSNs are often divided into clusters. This clustering approach reduces communication costs and the energy required for routing data packets. Consequently, selecting the most efficient cluster head (CH) is crucial for maximizing the network's overall lifespan. This paper proposes a protocol that prioritizes energy efficiency, proximity to the base station, and even distribution within clusters when selecting CHs for intra-cluster communication. For inter-cluster communication, the protocol draws inspiration from the SMO protocol to identify the optimal next-hop CH based on remaining energy and distance to the base station. The performance of this proposed protocol is then compared against LEACH routing protocols. The simulation results indicate that the network becomes more optimized and energy efficient by using the proposed protocol.

Cellular networks can overcome their bandwidth bottleneck problem through the use of device-to-device communication paradigm. In instances of traffic congestion and natural calamities, these technologies aid in preserving the essential connection between user devices. It overcomes the need for nearby user equipment (UEs) to send their radio signals through the BS or the core network to facilitate immediate information sharing. This work addresses relay-assisted device-to-device (D2D) communication in disaster scenarios. An adaptive architecture for D2D communications is developed that can be used in emergency conditions. In particular, fuzzy based a new nature-inspired squirrel search algorithm (SSA) is proposed for CH selection. By using this method, a UERCH is selected and the information is passed through this relay CH. To enable communication between victims of natural catastrophes and emergency personnel, the architecture uses an SDN controller to help it establish a multi-hop routing path. Additionally, we offer a public safety scenario in which a portion of the network goes down as a result of exceptional occurrences like natural disaster, showcasing the robustness and potential of our proposed method. On comparing with the existing approach, the simulation results show that the suggested method achieves low energy usage with enhanced device battery life.

Chord is a Distributed Hash Table widely used for its efficiency in searching for information. The efficiency of this structure relies on creating short paths of O(log2 n) between two nodes, in which n is the number of nodes. To enhance efficiency, several studies use replication in the nodes belonging to the network, assuming that searches will converge in these replicated nodes. This work proposes a convergence formula and analyzes the number of searches converging on nodes for different network sizes (small, medium, and large), up to one million nodes. The experiments show that the convergence creates three zones and the results support the replication techniques from previous studies and demonstrate that it is feasible to replicate in nodes that were not considered in these studies.

Cloud computing enables users to access required resources, with the invention of high-end devices leading to exponential increases in cloud resource requests. This poses significant challenges for resource management due to the scale of the cloud and unpredictable user demands. This paper presents an approach to managing resources during peak request periods for virtual machines (VMs) by leveraging cloud federation, outsourcing requests to other federation members. An algorithm is proposed to initiate cloud federation and allocate customer requests within it. The primary objectives are to increase the profit of cloud providers and improve resource utilization. An ensemble algorithm maximizes profit using both the proposed algorithm and three established ones. Experimental results demonstrate that our method outperforms existing approaches in profit, resource utilization, and rejected requests in most scenarios.